| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Focuses on how organisms grow in size and complexity, how developmental timing is regulated, how tissues regenerate after injury, and how organisms transition between major life-cycle stages (embryo → juvenile → adult → reproductive → senescent). Includes growth-rate control, hormonal and molecular timing pathways, regeneration programs, metamorphosis, molting, and developmental checkpoints. Excludes normal adult physiology unless it relates to growth or timing, and excludes ecological life-history strategy unless tied to developmental mechanisms. |
| | Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates across cellular, tissue, organ, organismal, and whole-life-cycle scales; temporal scales from minutes (injury-response initiation) to hours/days (regeneration or growth changes) to months/years (full life-cycle transitions). |
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Growth factors, hormones, stem cells, progenitors, differentiated cells, regeneration niches, morphogenetic signals, timing regulators (circadian clocks, developmental timers), checkpoints, blastema structures, life-stage modules (larval, juvenile, adult). |
| | Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Growth rate, proliferation capacity, regenerative potential, timing thresholds, hormone concentration, metabolic state, circadian phase, differentiation status, senescence markers, life-stage identity. |
| | Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Growth modes (isometric, allometric), timing systems (circadian, developmental, hormonal), regeneration types (epimorphic, compensatory, morphallactic), life-cycle stages (embryonic, larval, metamorphic, adult, senescent), checkpoint types (size, nutritional, developmental). |
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Cell-division frequency, tissue-growth rate, hormone levels, metabolic flux, injury-signal intensity, stem-cell activation state, regeneration progress index, checkpoint status, life-stage markers, circadian phase. |
| | Parameterization | How variables encode and represent the system’s state. | System state encoded via gene-expression programs, hormone-concentration curves, growth-rate equations, injury-response cascades, regeneration-trajectory models, timing-network dynamics, and life-stage transition matrices. |
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Treating growth as uniform across tissues; modeling regeneration as a single linear pathway; using simplified hormonal timing circuits; ignoring metabolic heterogeneity; approximating transitions as discrete instead of continuous; assuming perfect regenerative capacity in model organisms. |
| | Validity Conditions | The limits and contexts in which idealizations hold or break down. | Fail under strong tissue heterogeneity, incomplete regeneration, species-specific timing programs, metabolic instability, environmental perturbation, or gradual life-cycle transitions that violate sharp staging assumptions. |
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Growth follows regulated size-control logic; timing systems integrate internal and external cues; regeneration is governed by conserved injury-response modules; life-cycle transitions depend on coordinated hormonal, environmental, and genetic cues; checkpoints maintain developmental coherence. |
| | Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes stable developmental timers, sufficiently plastic stem-cell compartments for regeneration, interpretable injury signals, well-defined life-stage boundaries, and robust size-control mechanisms. |
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Growth models, timing pathways, regeneration frameworks, and life-cycle stage boundaries must not contradict one another; hormonal, metabolic, and genetic signals must align with observed developmental transitions. |
| | Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | Growth regulation, timing networks, injury-response programs, stem-cell behavior, metabolic constraints, and life-stage modules must integrate into a unified developmental system governing organismal progression through size, form, and age. |
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | Growth curves, size changes, proliferation rates, timing of developmental events, regeneration onset and progression, circadian or developmental oscillations, hormone-level changes, life-stage transitions (molting, metamorphosis), blastema formation, wound closure dynamics. |
| | Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Limited by ability to monitor internal growth in deep tissues, low sensitivity to early injury signals, difficulty detecting small stem-cell activation events, time-resolution limits for rapid circadian/timing oscillations, and inability to visualize early regeneration under opaque tissues. |
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | Microns/mm (size, growth), %/hour (proliferation), hormone concentration (ng/mL or nM), regeneration index (% restored), timing units (hours/days to transitions), circadian phase (degrees or hours), wound size (µm²), stem-cell activation markers (fluorescence intensity). |
| | Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | Live-imaging microscopes, growth-tracking platforms, hormone assays (ELISA, LC-MS), circadian reporters (bioluminescence/fluorescence), RNA-seq and ATAC-seq for regeneration profiling, wound-healing imaging systems, metabolic sensors, lineage-tracing tools, 3D organoid and tissue-regeneration imaging systems. |
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | Growth rate defined as change in size over time; regeneration defined by structural and functional restoration after injury; “life-stage” defined by stable physiological and morphological criteria; timing checkpoint defined by a requirement to progress to next developmental stage; circadian phase defined relative to oscillatory markers. |
| | Procedures | The explicit steps required to perform a measurement in a reproducible way. | Measuring size at repeated intervals, tracking cell-cycle markers, quantifying hormone levels, staging animals at life-cycle transitions, imaging regeneration progress, profiling injury-response genes, monitoring circadian reporters, performing lineage tracing during regrowth. |
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Standardized staging of organisms, controlled growth conditions, repeated sampling at defined timepoints, replicated injury/regeneration experiments, uniform hormone-assay protocols, consistent circadian entrainment conditions, precise imaging orientation and calibration. |
| | Sampling | Rules determining which subset of the domain is measured and how representative it is. | Sampling across developmental stages, across injured vs uninjured tissues, across circadian cycles, across regenerating timepoints, across organism sizes and ages, and across multiple individuals to account for stochastic variation in regeneration and timing. |
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | Growth curves, life-stage transition timelines, hormone-concentration profiles, regeneration-index trajectories, circadian oscillation traces, time-lapse regeneration images, transcriptional-response matrices, lineage-trees during regrowth. |
| | Resolution | The granularity or precision with which data is captured. | Determined by imaging frame rate, temporal spacing of measurements (timing precision), sequencing depth for regeneration profiling, hormone-assay sensitivity, and ability to resolve small changes in tissue repair or early-stage transitions. |
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Calibration of imaging magnification, hormone-assay standard curves, circadian-reporter normalization, wound-size measurement standards, growth-rate normalization, sequencing-based QC, alignment of developmental-stage scoring. |
| | Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Identification of measurement drift, stage-scoring inconsistency, hormone-assay noise, regeneration-index misclassification, variation in injury severity, circadian reporter variability, and separation of technical vs biological noise in growth and regeneration measurements. |
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Growth follows predictable size–rate relationships; timing pathways enforce ordered developmental checkpoints; regeneration proceeds through conserved injury-response, proliferation, and pattern-restoration phases; life-cycle transitions follow regulated hormonal and genetic switches; circadian timing entrains downstream processes with consistent periodicity. |
| | Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Conserved phases of regeneration (wound healing → blastema → redifferentiation); stable developmental-stage sequences; fixed order of timing checkpoints; invariant hormone-triggered transitions (e.g., metamorphic hormone surges); conserved growth-control logic across taxa. |
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Growth controlled by interplay of growth factors, nutrient sensing, and proliferation; timing governed by circadian clocks, hormonal cascades, and developmental timers; regeneration driven by injury signals, stem-cell activation, and patterning programs; life-cycle shifts initiated by endocrine and environmental cues. |
| | Pathways | Organized sequences of interactions forming a causal chain or network. | Injury → inflammation → blastema formation → proliferation → patterning → regrowth; developmental timing → checkpoint satisfaction → stage transition; hormone surge → widespread gene-regulatory shift → life-cycle change; nutrient signals → growth-rate modulation. |
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Growth rate, proliferation control, regeneration, blastema, developmental timing, circadian clock, checkpoint, metamorphosis, molting, life-stage, hormonal regulation, plasticity, redifferentiation, competence windows. |
| | Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Growth types (isometric, allometric), regeneration modes (epimorphic, compensatory, morphallactic), timing systems (circadian, developmental, hormonal), life-cycle transitions (larval, juvenile, adult, metamorphic, senescent), checkpoint types (size, nutritional, molecular). |
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | Growth equations (logistic, exponential), hormonal-dynamics ODEs, circadian oscillation models, regeneration-trajectory functions, checkpoint-threshold equations, injury-response activation curves, nutrient–growth rate relationships. |
| | Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | Circadian oscillator models, endocrine-transition models, injury–regeneration GRN models, growth-curve models, metamorphosis-switch models, agent-based regeneration simulations, stage-transition Markov models. |
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Treating tissues as homogeneous; assuming perfect regeneration; ignoring metabolic or environmental variation; approximating life-cycle transitions as discrete jumps; modeling timing systems as deterministic rather than noisy; reducing endocrine networks to single master regulators. |
| | Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Fail with strong heterogeneity in tissue response, incomplete or species-specific regeneration, environmental disruption of timing, nonlinear dynamics in endocrine pathways, or gradual life-cycle transitions not captured by discrete-stage approximations. |
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Growth, timing, regeneration, and life-cycle transitions integrate through intertwined hormonal, genetic, metabolic, and environmental inputs; injury-response frameworks and developmental-timing models unify under conserved regulatory architectures; circadian and developmental clocks interact to coordinate organismal progression. |
| | Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Connects to endocrinology (hormonal pathways), systems biology (regulatory networks), physiology (growth and metabolism), regenerative medicine (tissue repair), ecology (life-history interactions), and evolutionary biology (divergence of life-cycle strategies). |
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Manipulating growth factors, altering hormone levels, shifting circadian phase, inducing controlled injuries, modifying nutrient availability, or genetically perturbing timing regulators to test causal roles in growth, regeneration, and developmental timing. |
| | Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Monitoring natural growth curves, documenting unperturbed regeneration, tracking spontaneous life-stage transitions, recording circadian oscillations, and observing timing-linked developmental events across individuals. |
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Testing whether growth-rate changes match predictions from nutrient/hormonal manipulation; validating regeneration-phase models; evaluating the necessity/sufficiency of timing regulators; testing circadian entrainment hypotheses; comparing predicted vs observed injury-response trajectories. |
| | Replication | The requirement that results be independently reproducible under similar conditions. | Repeating regeneration assays, replicating hormone-level measurements, re-running growth-rate tracking, validating circadian-phase shifts, and confirming life-stage transitions across independent cohorts. |
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Estimating growth-rate constants, fitting regeneration curves, calculating timing thresholds, analyzing circadian phase shifts, modeling injury-response dynamics, and quantifying uncertainty in stage-transition timing. |
| | Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Comparing growth models (linear, logistic, exponential), competing regeneration frameworks (epimorphic vs compensatory), different endocrine-transition models, deterministic vs stochastic timing circuits, and alternative circadian oscillator models. |
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Identifying measurement drift in longitudinal imaging, hormone-assay noise, staging inconsistencies, injury-severity variation, regeneration-index misclassification, circadian reporter variability, and technical vs biological noise. |
| | Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Standardizing injury procedures, synchronizing circadian conditions, controlling nutrient and environmental variables, blinding scoring of growth and regeneration, validating markers, and normalizing sequencing or assay data across batches. |
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Reanalyzing datasets with independent pipelines, validating timing-network predictions externally, cross-checking endocrine-model assumptions, comparing regeneration results across species/systems, and revising conclusions when contradictions arise. |
| | Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Updating growth/regeneration models when new mechanisms appear, revising timing-network architecture when oscillations deviate from predictions, adjusting endocrine-transition models when alternative pathways emerge, and modifying life-cycle frameworks based on new evidence. |
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Full reporting of growth conditions, injury protocols, timing manipulations, hormone assays, imaging/sequence parameters, analytical pipelines, and uncertainty sources; sharing raw and intermediate data where possible. |
| | Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Ethical treatment of organisms during injury or regenerative studies, adherence to life-stage manipulation limits, accurate and honest data reporting, avoidance of selective omissions, and compliance with developmental/regenerative-biology standards. |